1. Field of the Invention
The present invention relates to a method of coding data, and more particularly, to a method of removing blocking artifacts when coding image signals such as in a moving picture at low-bit-rate.
2. Background of the Related Art
Generally, to efficiently compress a time variable video sequence, it is necessary to remove redundancy in the temporal domain as well as in the two-dimensional spatial domain. In moving picture experts group (MPEG), discrete cosine transform (DCT) is used to remove the redundancy in the two-dimensional spatial domain while a motion compensation method is used to remove the redundancy in the temporal domain.
The DCT is a method of removing the correlativity between data through a two-dimensional spatial transformation. Each block in a picture is spatially transformed using the DCT after the picture is divided into blocks. Data that has been spatially transformed tends to be driven to a certain direction. Only a group of the data driven in the certain direction is quantized and transmitted.
Pictures, which are consecutive in the temporal domain, tend to form motions of a human being or an object at the center of the frame. This property is used to reduce the redundancy of the temporal domain in the motion compensation method. A volume of data to be transmitted can be minimized by taking out a similar region from the preceding picture to fill a corresponding region, which has not been changed (or has very little change), in the present picture. The operation of finding the most similar blocks between pictures is called a motion estimation. The displacement representing a degree of motion is called a motion vector. MPEG uses a motion compensation-DCT method so that the two methods combine.
When a compression technique is combined with a DCT algorithm, the DCT transform is usually performed after input data is sampled in a unit size of 8.times.8, and the transform coefficients are quantized with respect to a visual property using quantization values from a quantization table. Then, the data is compressed through a run length coding (RLC). The data processed with the DCT is converted from a spatial domain to a frequency domain and compressed through the quantization with respect to the visual property of human beings, not to be visually recognized. For example, since eyes of human beings are insensitive to a high frequency, a high frequency coefficient is quantized in a large step size.
For the quantized data, the data having a relatively high frequency is coded with a short code word. The quantized data having a low frequency is coded with a long code word. Thus, the data is finally compressed.
In processing a moving picture as discussed above, blocks are individually processed to maximize the compression ratio and coding efficiency. However, the individual process causes blocking artifacts that disturb the eyes of human beings at boundaries between blocks.
A related art method of removing blocking artifacts will be described with reference to FIGS. 1 and 2. FIG. 1 is a pixel matrix illustrating a method for removing blocking artifacts. FIG. 2 is a pixel matrix illustrating block boundaries in horizontal and vertical directions.
Various algorithms have been presented for removing blocking artifacts that appear in a coding system, which individually processes blocks. For example, MPEG-4 used a deblocking filter by Telenor, which uses the following algorithm:
If B is replaced with B1 and C is replaced with C1, PA1 B1=B+d1, PA1 C1=C-d1, and PA1 d1=sign(d)*(MAX(0,.vertline.d.vertline.-MAX(0,2*.vertline.d.vertline.-QP))) PA1 If m&lt;1; PA1 v.sub.m, if 1.ltoreq.m.ltoreq.8; PA1 (.vertline.v.sub.8 -v.sub.9.vertline.&lt;QP) v.sub.9 :v.sub.8, if m&gt;8; PA1 {b.sub.k :-4.ltoreq.k.ltoreq.4}={1,1,2,2,4,2,2,1,1}//16,
where d=(3A-8B+8C-3D)/16 and QP denotes the quantization parameter of the macroblock where pixel C belongs.
In processing a MPEG-4 moving picture, blocking artifacts are removed using the above algorithm to improve picture quality. However, it is difficult to effectively remove the blocking artifacts with the above with a small operation capacity in a real time operation. For example, coding and decoding a moving picture is a real time operation. In other words, to completely remove the blocking artifacts, a large calculation amount is needed, which is undesirable in efficiency.
Alternatively, to remove the blocking artifacts, there is provided a method of changing processes of coding and decoding. This method increases the amount of bits to be transmitted.
Still another method for removing blocking artifacts is based on the theory of projection onto convex sets (POCS). However, this method is applied only to a still picture because of an iteration structure and long convergence time.
Thus, the related art methods for removing blocking artifacts in a coding system of a moving picture have several problems. First, in performing an algorithm for removing the blocking artifacts, a calculation is complicated and the calculation amount and time become correspondingly large. Further, the blocking artifacts are not removed in either complex regions or smooth regions in a picture. In addition, the amount of bits to be transmitted increases.